The pseudo-self-similar traffic model: application and validation

  • Authors:
  • Rachid El Abdouni Khayari;Ramin Sadre;Boudewijn R. Haverkort;Alexander Ost

  • Affiliations:
  • Department of Computer Science, University of the Federal Armed Forces Munich, 85577 Neubiberg, Germany;Department of Computer Science, RWTH Aachen, 52056 Aachen, Germany;Department of Electrical Engineering, Mathematics and Computer Science, University of Twente, 7500 AE Enschede, The Netherlands;Ericsson Eurolab Germany, 52134 Herzogenrath, Germany

  • Venue:
  • Performance Evaluation - Dependable systems and networks-performance and dependability symposium (DSN-PDS) 2002: Selected papers
  • Year:
  • 2004

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Abstract

Since the early 1990s, a variety of studies have shown that network traffic, both for local- and wide-area networks, has self-similar properties. This led to new approaches in network traffic modelling because most traditional traffic approaches result in the underestimation of performance measures of interest. Instead of developing completely new traffic models, a number of researchers have proposed to adapt traditional traffic modelling approaches to incorporate aspects of self-similarity. The motivation for doing so is the hope to be able to reuse techniques and tools that have been developed in the past and with which experience has been gained. One such approach is the so-called pseudo-self-similar traffic (PSST) model. This model is appealing, as it is easy to understand and easily embedded in Markovian performance evaluation studies.In applying this model in a number of cases, we have perceived various problems which we initially thought were particular to these specific cases. However, we recently have been able to show that these problems are fundamental to the PSST model.In this paper we review the PSST model, validate it experimentally and discuss its shortcomings. As far as we know, this is the first paper that discusses these shortcomings formally. We also report on ongoing work to overcome some of these problems.